The objective of this study is to compare the normalized prediction distribution errors (NPDE) and the visual predictive check (VPC) on model evaluation under different study designs. In this study, simulation method was utilized to investigate the capability of NPDE and VPC to evaluate the models. Data from the false models were generated by biased parameter typical value or inaccurate parameter inter-individual variability after single or multiple doses with the same sampling time or multiple doses with varied sampling time, respectively. The results showed that there was no clear statistic test for VPC and it was difficult to make sense of VPC under the multiple doses with varied sampling time. However, there were corresponding statistic tests for NPDE and the factor of study design did not affect NPDE significantly. It suggested that the clinical data and model which VPC was not fit for could be evaluated by NPDE.

This study is to develop a therapeutic drug monitoring (TDM) network server of tacrolimus for Chinese renal transplant patients, which can facilitate doctor to manage patients' information and provide three levels of predictions. Database management system MySQL was employed to build and manage the database of patients and doctors' information, and hypertext mark-up language (HTML) and Java server pages (JSP) technology were employed to construct network server for database management. Based on the population pharmacokinetic model of tacrolimus for Chinese renal transplant patients, above program languages were used to construct the population prediction and subpopulation prediction modules. Based on Bayesian principle and maximization of the posterior probability function, an objective function was established, and minimized by an optimization algorithm to estimate patient's individual pharmacokinetic parameters. It is proved that the network server has the basic functions for database management and three levels of prediction to aid doctor to optimize the regimen of tacrolimus for Chinese renal transplant patients.

Pharmacometrics,developed from the conventional pharmacokinetics,is the science of applying mathe-matical and statistical methods to characterize,understand,and predict a drug's pharmacokinetic,phannacodyna-mic,and biomarker-outcome behaviors.Pharmacometrics has been widely valued for its utility of modeling and simulation in drug research and development,therapeutic drug monitoring and individualized therapy.This paper reviewed the advances of pharmacometrics employed in new drug research and development and therapeutic drug monitoring both at home and abroad.

Objective: To assess the private hospital development in China from 2005 to 2016 from a global perspective. Methods: We searched the English and Chinese literature in PubMed, CNKI and Google Scholar databases with the keywords including "private hospitals in China", "hospital ownership", "public and private hospital", "private hospital development". Descriptive statistical analysis was used to assess the trend of the private hospital development in China and worldwide. Both the change of private hospitals in supply capacity and health care delivery were studied in this paper. The number of hospitals, number of hospital beds and the average number of hospital beds per hospital were employed to measure the supply capacity. The visit number, inpatients number, and bed occupancy rate (BOR) were used to measure the healthcare delivery. The data was collected from the China Health Statistical Yearbook and the website of Organisation for Economic and Co-operation and Development (OECD) Statistics. Results: The private sector rapidly expanded in China's hospital market in recent years. The number of private hospitals exceeded the public sectors in 2015. There has also been a signifi cant rise for the indicators of both the supply capacity (including number of hospitals, number of hospital beds and the average number of hospital beds per hospital) and the health care delivery (inpatients number and BOR) of the private hospitals. However, the growth rates of them were relatively lower than the public. The expansion trend of China's private sector in the hospital market accorded with most the OECD countries around the world. In 2016, China was above the medium level of the share of the private hospitals' number with the OECD countries, but below the medium for the supply capacity, in terms of the hospital beds. Conclusion: As a result of the economic growth and supporting policy, the private sector has experienced a vast expansion in China's hospital market in the past decade. The rising gap in average size between private and publicly owned hospitals, and the inconsistent development between the private hospitals' supply capacity and their market share, have become the two main challenges. Meanwhile, the future policy in supporting the private sector should be carefully introduced to advance the whole healthcare delivery system development in China.

Objective:To investigate the prevalence and influencing factors of mental health status and internet-surfing behavior among rural adolescents in Sichuan province,and explore the mutual effects between mental health status and internet-surfing behavior.Methods:Totally 2745 junior and senior high school students of grade seven and grade ten from two rural schools were selected.Mental health status,self-esteem and social support of students were assessed with Mental Health Inventory of Middle-school students (MMHI),Rosenberg self-esteem scale (SES) and social support rating scale (SSRS) respectively.Demographic characteristics,internet-surfing behavior were obtained using cross-sectional survey.Non-recursive structural equation model was applied to analyze the effects of other variables on mental health status and internet-surfing behavior and the mutual effects between them.Results:The mean score of MMHIwas (2.1 ±0.7),and the dimensions including academic stress (2.4 ±0.9),emotional instability (2.4 ±0.8) and anxiety (2.4 ± 1.0) got the top three.The total prevalence of long-time internet-surfing was 32.8％ (899/2745).The structural equation model showed that female and increasing age had positive effects on score of MMHI (β =0.058,0.058,P ＜ 0.001),and male and increasing age positively influenced internet-surfing behavior (β =-0.171,0.149,P ＜ 0.001).The scores of SES and S SRS were directly negatively related to the score of MMHI (β =-0.300,-0.263,P ＜ 0.001),and indirectly negatively affect internetsurfing behavior through the mediating effect of mental health (βi =-0.074,-0.065,P ＜ 0.010).The score of MMHI had positively effects on long-time internet-surfing behavior (β =0.246,P ＜ 0.001),and long-time internetsurfing behavior had positively effects on the score of MMHI in reverse (β =0.008,P ＜ 0.001),but much weaker.Conclusion:There are mild mental health problem among rural adolescents,and internet-surfing behaviors are prevalent among this population.Poor mental health and long-time internet-surfing behavior are risk factors mutually.

The gut microbiota plays a pivotal role in the immunomodulatory and protumorigenic microenviron-ment of colorectal cancer(CRC).However,the effect of ginsenoside Rk3(Rk3)on CRC and gut microbiota remains unclear.Therefore,the purpose of this study is to explore the potential effect of Rk3 on CRC from the perspective of gut microbiota and immune regulation.Our results reveal that treatment with Rk3 significantly suppresses the formation of colon tumors,repairs intestinal barrier damage,and regulates the gut microbiota imbalance caused by CRC,including enrichment of probiotics such as Akkermansia muciniphila and Barnesiella intestinihominis,and clearance of pathogenic Desulfovibrio.Subsequent metabolomics data demonstrate that Rk3 can modulate the metabolism of amino acids and bile acids,particularly by upregulating glutamine,which has the potential to regulate the immune response.Furthermore,we elucidate the regulatory effects of Rk3 on chemokines and inflammatory factors associated with group 3 innate lymphoid cells(ILC3s)and T helper 17(Th17)signaling pathways,which inhibits the hyperactivation of the Janus kinase-signal transducer and activator of transcription 3(JAK-STAT3)signaling pathway.These results indicate that Rk3 modulates gut microbiota,regulates ILC3s immune response,and inhibits the JAK-STAT3 signaling pathway to suppress the development of colon tumors.More importantly,the results of fecal microbiota transplantation suggest that the inhibitory effect of Rk3 on colon tumors and its regulation of ILC3 immune responses are mediated by the gut microbiota.In summary,these findings emphasize that Rk3 can be utilized as a regulator of the gut microbiota for the prevention and treatment of CRC.

Objective:To analyze the morphology and molecular biology and clarify the taxonomic status of one Cupriavidus species strain SZY C1 isolated from clinical wound specimens. Methods:Strain SZY C1 was subjected to physiological and biochemical identification, 16S rRNA gene sequencing, and whole genome sequencing. Its genomic features and virulence genes were analyzed using bioinformatics software.Results:Strain SZY C1 was a gram-negative, non-fermenting bacterium wihout flagella and the ability to form spores. After culturing on Columbia blood agar plates for 24 h, it formed grayish-white colonies that were round, raised, opaque, and had neatly defined margins. Based on 16S rRNA gene sequence analysis, strain SZY C1 belonged to the genus Cupriavidus with the highest 98.52% similarity to Cupriavidus metallicuns. The genome size of strain SZY C1 was determined to be 5 515 517 bp, with a G+ C content of 67.87%. Whole genome sequencing showed that strain SZY C1 had the closest phylogenetic relationship with Cupriavidus agavae, with an average nucleotide identity value of 84.76% and a digital DNA-DNA hybridization value of 29.1%, which were lower than the identification threshold for prokaryotic species. The strain SZY C1 carried multiple virulence genes, drug resistance genes, and heavy metal resistance genes. Conclusions:Based on phenotypic and genomic analyses, the strain SZY C1 is a potential new species of the Cupriavidus genus.

With the increasing cost of drug development and clinical trials, it is of great value to make full use of all kinds of data to improve the efficiency of drug development and to provide valid information for medication guidelines. Model-based meta-analysis (MBMA) combines mathematical models with meta-analysis to integrate information from multiple sources (preclinical and clinical data, etc.) and multiple dimensions (targets/mechanisms, pharmacokinetics/pharmacodynamics, diseases/indications, populations, regimens, biomarkers/efficacy/safety, etc.), which not only provides decision-making for all key points of drug development, but also provides effective information for rational drug use and cost-effectiveness analysis. The classical meta-analysis requires high homogeneity of the data, while MBMA can combine and analyze the heterogeneous data of different doses, different time courses, and different populations through modeling, so as to quantify the dose-effect relationship, time-effect relationship, and the relevant impact factors, and thus the efficacy or safety features at the level of dose, time and covariable that have not been involved in previous studies. Although the modeling and simulation methods of MBMA are similar to population pharmacokinetics/pharmacodynamics (Pop PK/PD), compared with Pop PK/PD, the advantage of MBMA is that it can make full use of literature data, which not only improves the strength of evidence, but also can answer the questions that have not been proved or can not be answered by a single study. At present, MBMA has become one of the important methods in the strategy of model-informed drug development (MIDD). This paper will focus on the application value, data analysis plan, data acquisition and processing, data analysis and reporting of MBMA, in order to provide reference for the application of MBMA in drug development and clinical practice.